Računska ocena vpliva znotrajceličnih presnovnih in signalnih poti ter medcelične komunikacije na izločanje glukagona in inzulina : doktorska disertacija

slovenian

doktorska dela

2022

Univerza v Mariboru, Fakulteta za naravoslovje in matematiko

This doctoral dissertation examines the physiological properties of alpha and beta cells using mathematical modeling, network science, and other contemporary biophysical approaches. The first part of the dissertation presents a newly developed mathematical model of metabolism and hormone secretion in both cell types. The model results indicate that the oxidation of fatty acids is responsible for the high basal production of ATP, while the glucose-dependent increase in ATP is due to the anaerobic (glycolytic) characteristics of the alpha cell or aerobic (mitochondrial) characteristics of the beta cell. Disturbances in glycolytic and mitochondrial metabolism appear to critically influence proper hormone secretion of both cell types. The alpha cell model is further complemented by the cAMP-dependent signaling pathway regulated by metabolic activity or in response to the binding of extracellular signals to membrane receptors. According to the model prediction, acidification of the intracellular space during high metabolic activity is crucial in lowering intracellular cAMP concentration under high plasma glucose concentration conditions. Moreover, the alpha cell model implements the effect of amino acids on alpha cell's activity, matching experimental observation that mixed nutrient challenge potently amplifies glucagon secretion. The second part of the dissertation presents the analysis of the experimentally-obtained calcium signals from beta cells in the islets of Langerhans. The presented data processing methodology includes extraction of metabolically-activated slow and electrically-activated fast components, binarization or discretization of signals, detection of low-quality signals, and construction of functional networks. Slow and fast oscillatory components are interrelated, with the frequency of fast oscillations being highest around the peaks of slow oscillations. This behavior is more pronounced during stimulation with physiological glucose concentration than with supraphysiological concentration. Functional networks are constructed for both components, and their analysis shows more local clustering and segregation of the networks of the fast component and greater globality of the slow component. Multilayer network analysis also indicates a weak coupling between the fast and slow layers, suggesting that different synchronization mechanisms shape the collective activity in the islets.

08.08.2023